You should use the git branch barry/2023-09-15/fix-log-pcmpi It is still work-in-progress but much better than what is currently in the main PETSc branch.
By default, the MPI linear solver server requires 10,000 unknowns per MPI process, so for smaller problems, it will only run on one MPI rank and list Sequential in your output. In general you need on the order of at least 10,000 unknowns per MPI process to get good speedup. You can control it with -mpi_linear_solver_server_minimum_count_per_rank <number_unknowns> Regarding the report of 1 iteration, that is fixed in the branch listed above. Barry > On Apr 26, 2024, at 5:11 PM, Yongzhong Li <[email protected]> > wrote: > > Hi Barry, > > Thanks, I am interested in this PCMPI solution provided by PETSc! > > I tried the src/ksp/ksp/tutorials/ex1.c which is configured in CMakelists as > follows: > > ./configure PETSC_ARCH=config-debug --with-scalar-type=complex > --with-fortran-kernels=1 --with-debugging=0 --with-logging=0 --with-cxx=g++ > --download-mpich --download-superlu --download-opencascade > --with-openblas-include=${OPENBLAS_INC} --with-openblas-lib=${OPENBLAS_LIB} > > In the linux terminal, my bash script is as follows, > > mpiexec -n 4 ./ex1 -mpi_linear_solver_server -mpi_linear_solver_server_view > > However, I found the ouput a bit strange > > Norm of error 1.23629e-15, Iterations 1 > MPI linear solver server statistics: > Ranks KSPSolve()s Mats KSPs Avg. Size Avg. > Its > Sequential 3 2 10 1 > Norm of error 1.23629e-15, Iterations 1 > MPI linear solver server statistics: > Ranks KSPSolve()s Mats KSPs Avg. Size Avg. > Its > Sequential 3 2 10 1 > Norm of error 1.23629e-15, Iterations 1 > MPI linear solver server statistics: > Ranks KSPSolve()s Mats KSPs Avg. Size Avg. > Its > Sequential 3 2 10 1 > Norm of error 1.23629e-15, Iterations 1 > MPI linear solver server statistics: > Ranks KSPSolve()s Mats KSPs Avg. Size Avg. > Its > Sequential 3 2 10 1 > > It seems that mpi started four processes, but they all did the same things, > and I am confused why the ranks showed sequential. Are these supposed to be > the desired output when the mpi_linear_solver_server is turned on? > > And if I run ex1 without any hypen options, I got > > Norm of error 2.47258e-15, Iterations 5 > > It looks like the KSPSolver use 5 iterations to reach convergence, but why > when mpi_linear_solver_server is enabled, it uses 1? > > I hope to get some help on these issues, thank you! > > Sincerely, > Yongzhong > > > > > From: Barry Smith <[email protected] <mailto:[email protected]>> > Date: Tuesday, April 23, 2024 at 5:15 PM > To: Yongzhong Li <[email protected] > <mailto:[email protected]>> > Cc: [email protected] <mailto:[email protected]> > <[email protected] <mailto:[email protected]>>, > [email protected] <mailto:[email protected]> > <[email protected] <mailto:[email protected]>>, Piero Triverio > <[email protected] <mailto:[email protected]>> > Subject: Re: [petsc-maint] Inquiry about Multithreading Capabilities in > PETSc's KSPSolver > > > Yes, only the routines that can explicitly use BLAS have multi-threading. > > PETSc does support using nay MPI linear solvers from a sequential (or > OpenMP) main program using the > https://urldefense.us/v3/__https://petsc.org/release/manualpages/PC/PCMPI/*pcmpi__;Iw!!G_uCfscf7eWS!ZuPZtoeGFKUjdTAW0Ylzhjz0KaqtPKAf4ZOa1Xahj_4JUS8wwupZKDb_BQCWgFWPJIYRFlA3dTDHsu8HNnxbn4Q$ > construct. I am finishing up better support in the branch > barry/2023-09-15/fix-log-pcmpi > > Barry > > > > > > > > On Apr 23, 2024, at 3:59 PM, Yongzhong Li <[email protected] > <mailto:[email protected]>> wrote: > > Thanks Barry! Does this mean that the sparse matrix-vector products, which > actually constitute the majority of the computations in my GMRES routine in > PETSc, don’t utilize multithreading? Only basic vector operations such as > VecAXPY and VecDot or dense matrix operations in PETSc will benefit from > multithreading, is it correct? > > Best, > Yongzhong > > From: Barry Smith <[email protected] <mailto:[email protected]>> > Date: Tuesday, April 23, 2024 at 3:35 PM > To: Yongzhong Li <[email protected] > <mailto:[email protected]>> > Cc: [email protected] <mailto:[email protected]> > <[email protected] <mailto:[email protected]>>, > [email protected] <mailto:[email protected]> > <[email protected] <mailto:[email protected]>>, Piero Triverio > <[email protected] <mailto:[email protected]>> > Subject: Re: [petsc-maint] Inquiry about Multithreading Capabilities in > PETSc's KSPSolver > > 你通常不会收到来自 [email protected] <mailto:[email protected]> 的电子邮件。了解这一点为什么很重要 > <https://urldefense.us/v3/__https://aka.ms/LearnAboutSenderIdentification__;!!G_uCfscf7eWS!ZuPZtoeGFKUjdTAW0Ylzhjz0KaqtPKAf4ZOa1Xahj_4JUS8wwupZKDb_BQCWgFWPJIYRFlA3dTDHsu8HDnoVup0$ > > > > Intel MKL or OpenBLAS are the best bet, but for vector operations they > will not be significant since the vector operations do not dominate the > computations. > > > On Apr 23, 2024, at 3:23 PM, Yongzhong Li <[email protected] > <mailto:[email protected]>> wrote: > > Hi Barry, > > Thank you for the information provided! > > Do you think different BLAS implementation will affect the multithreading > performance of some vectors operations in GMERS in PETSc? > > I am now using OpenBLAS but didn’t see much improvement when theb > multithreading are enabled, do you think other implementation such as netlib > and intel-mkl will help? > > Best, > Yongzhong > > From: Barry Smith <[email protected] <mailto:[email protected]>> > Date: Monday, April 22, 2024 at 4:20 PM > To: Yongzhong Li <[email protected] > <mailto:[email protected]>> > Cc: [email protected] <mailto:[email protected]> > <[email protected] <mailto:[email protected]>>, > [email protected] <mailto:[email protected]> > <[email protected] <mailto:[email protected]>>, Piero Triverio > <[email protected] <mailto:[email protected]>> > Subject: Re: [petsc-maint] Inquiry about Multithreading Capabilities in > PETSc's KSPSolver > > 你通常不会收到来自 [email protected] <mailto:[email protected]> 的电子邮件。了解这一点为什么很重要 > <https://urldefense.us/v3/__https://aka.ms/LearnAboutSenderIdentification__;!!G_uCfscf7eWS!ZuPZtoeGFKUjdTAW0Ylzhjz0KaqtPKAf4ZOa1Xahj_4JUS8wwupZKDb_BQCWgFWPJIYRFlA3dTDHsu8HDnoVup0$ > > > > PETSc provided solvers do not directly use threads. > > The BLAS used by LAPACK and PETSc may use threads depending on what BLAS > is being used and how it was configured. > > Some of the vector operations in GMRES in PETSc use BLAS that can use > threads, including axpy, dot, etc. For sufficiently large problems, the use > of threaded BLAS can help with these routines, but not significantly for the > solver. > > Dense matrix-vector products MatMult() and dense matrix direct solvers > PCLU use BLAS and thus can benefit from threading. The benefit can be > significant for large enough problems with good hardware, especially with > PCLU. > > If you run with -blas_view PETSc tries to indicate information about the > threading of BLAS. You can also use -blas_num_threads <n> to set the number > of threads, equivalent to setting the environmental variable. For dense > solvers you can vary the number of threads and run with -log_view to see what > it helps to improve and what it does not effect. > > > > > On Apr 22, 2024, at 4:06 PM, Yongzhong Li <[email protected] > <mailto:[email protected]>> wrote: > > This Message Is From an External Sender > This message came from outside your organization. > Hello all, > > I am writing to ask if PETSc’s KSPSolver makes use of OpenMP/multithreading, > specifically when performing iterative solutions with the GMRES algorithm. > > The questions appeared when I was running a large numerical program based on > boundary element method. I used the PETSc's GMRES algorithm in KSPSolve to > solve a shell matrix system iteratively. I observed that threads were being > utilized, controlled by the OPENBLAS_NUM_THREADS environment variable. > However, I noticed no significant performance difference between running the > solver with multiple threads versus a single thread. > > Could you please confirm if GMRES in KSPSolve leverages multithreading, and > also whether it is influenced by the multithreadings of the low-level math > libraries such as BLAS and LAPACK? If so, how can I enable multithreading > effectively to see noticeable improvements in solution times when using > GMRES? If not, why do I observe that threads are being used during the GMERS > solutions? > > For reference, I am using PETSc version 3.16.0, configured in CMakelists as > follows: > > ./configure PETSC_ARCH=config-release --with-scalar-type=complex > --with-fortran-kernels=1 --with-debugging=0 COPTFLAGS=-O3 -march=native > CXXOPTFLAGS=-O3 -march=native FOPTFLAGS=-O3 -march=native --with-cxx=g++ > --download-openmpi --download-superlu --download-opencascade > --with-openblas-include=${OPENBLAS_INC} --with-openblas-lib=${OPENBLAS_LIB} > --with-threadsafety --with-log=0 --with-openmp > > To simplify the diagnosis of potential issues, I have also written a small > example program using GMRES to solve a sparse matrix system derived from a 2D > Poisson problem using the finite difference method. I found similar issues on > this piece of codes. The code is as follows: > > #include <petscksp.h> > > /* Monitor function to print iteration number and residual norm */ > PetscErrorCode MyKSPMonitor(KSP ksp, PetscInt n, PetscReal rnorm, void *ctx) { > PetscErrorCode ierr; > ierr = PetscPrintf(PETSC_COMM_WORLD, "Iteration %D, Residual norm %g\n", > n, (double)rnorm); > CHKERRQ(ierr); > return 0; > } > > int main(int argc, char **args) { > Vec x, b, x_true, e; > Mat A; > KSP ksp; > PetscErrorCode ierr; > PetscInt i, j, Ii, J, n = 500; // Size of the grid n x n > PetscInt Istart, Iend, ncols; > PetscScalar v; > PetscMPIInt rank; > PetscInitialize(&argc, &args, NULL, NULL); > PetscLogDouble t1, t2; // Variables for timing > MPI_Comm_rank(PETSC_COMM_WORLD, &rank); > > // Create vectors and matrix > ierr = VecCreateMPI(PETSC_COMM_WORLD, PETSC_DECIDE, n*n, &x); > CHKERRQ(ierr); > ierr = VecDuplicate(x, &b); CHKERRQ(ierr); > ierr = VecDuplicate(x, &x_true); CHKERRQ(ierr); > > // Set true solution as all ones > ierr = VecSet(x_true, 1.0); CHKERRQ(ierr); > > // Create and assemble matrix A for the 2D Laplacian using 5-point stencil > ierr = MatCreate(PETSC_COMM_WORLD, &A); CHKERRQ(ierr); > ierr = MatSetSizes(A, PETSC_DECIDE, PETSC_DECIDE, n*n, n*n); > CHKERRQ(ierr); > ierr = MatSetFromOptions(A); CHKERRQ(ierr); > ierr = MatSetUp(A); CHKERRQ(ierr); > ierr = MatGetOwnershipRange(A, &Istart, &Iend); CHKERRQ(ierr); > for (Ii = Istart; Ii < Iend; Ii++) { > i = Ii / n; // Row index > j = Ii % n; // Column index > v = -4.0; > ierr = MatSetValues(A, 1, &Ii, 1, &Ii, &v, INSERT_VALUES); > CHKERRQ(ierr); > if (i > 0) { // South > J = Ii - n; > v = 1.0; > ierr = MatSetValues(A, 1, &Ii, 1, &J, &v, INSERT_VALUES); > CHKERRQ(ierr); > } > if (i < n - 1) { // North > J = Ii + n; > v = 1.0; > ierr = MatSetValues(A, 1, &Ii, 1, &J, &v, INSERT_VALUES); > CHKERRQ(ierr); > } > if (j > 0) { // West > J = Ii - 1; > v = 1.0; > ierr = MatSetValues(A, 1, &Ii, 1, &J, &v, INSERT_VALUES); > CHKERRQ(ierr); > } > if (j < n - 1) { // East > J = Ii + 1; > v = 1.0; > ierr = MatSetValues(A, 1, &Ii, 1, &J, &v, INSERT_VALUES); > CHKERRQ(ierr); > } > } > ierr = MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); > ierr = MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); > > // Compute the RHS corresponding to the true solution > ierr = MatMult(A, x_true, b); CHKERRQ(ierr); > > // Set up and solve the linear system > ierr = KSPCreate(PETSC_COMM_WORLD, &ksp); CHKERRQ(ierr); > ierr = KSPSetOperators(ksp, A, A); CHKERRQ(ierr); > ierr = KSPSetType(ksp, KSPGMRES); CHKERRQ(ierr); > ierr = KSPSetTolerances(ksp, 1e-5, PETSC_DEFAULT, PETSC_DEFAULT, > PETSC_DEFAULT); CHKERRQ(ierr); > > /* Set up the monitor */ > ierr = KSPMonitorSet(ksp, MyKSPMonitor, NULL, NULL); CHKERRQ(ierr); > > // Start timing > PetscTime(&t1); > > ierr = KSPSolve(ksp, b, x); CHKERRQ(ierr); > > // Stop timing > PetscTime(&t2); > > // Compute error > ierr = VecDuplicate(x, &e); CHKERRQ(ierr); > ierr = VecWAXPY(e, -1.0, x_true, x); CHKERRQ(ierr); > PetscReal norm_error, norm_true; > ierr = VecNorm(e, NORM_2, &norm_error); CHKERRQ(ierr); > ierr = VecNorm(x_true, NORM_2, &norm_true); CHKERRQ(ierr); > PetscReal relative_error = norm_error / norm_true; > if (rank == 0) { // Print only from the first MPI process > PetscPrintf(PETSC_COMM_WORLD, "Relative error ||x - x_true||_2 / > ||x_true||_2: %g\n", (double)relative_error); > } > > // Output the wall time taken for MatMult > PetscPrintf(PETSC_COMM_WORLD, "Time taken for KSPSolve: %f seconds\n", t2 > - t1); > > // Cleanup > ierr = VecDestroy(&x); CHKERRQ(ierr); > ierr = VecDestroy(&b); CHKERRQ(ierr); > ierr = VecDestroy(&x_true); CHKERRQ(ierr); > ierr = VecDestroy(&e); CHKERRQ(ierr); > ierr = MatDestroy(&A); CHKERRQ(ierr); > ierr = KSPDestroy(&ksp); CHKERRQ(ierr); > PetscFinalize(); > return 0; > } > > Here are some profiling results for GMERS solution. > > OPENBLAS_NUM_THREADS = 1, iteration steps = 859, solution time = 16.1 > OPENBLAS_NUM_THREADS = 2, iteration steps = 859, solution time = 16.3 > OPENBLAS_NUM_THREADS = 4, iteration steps = 859, solution time = 16.7 > OPENBLAS_NUM_THREADS = 8, iteration steps = 859, solution time = 16.8 > OPENBLAS_NUM_THREADS = 16, iteration steps = 859, solution time = 17.8 > > I am using one workstation with Intel® Core™ i9-11900K Processor, 8 cores, 16 > threads. Note that I am not using multiple MPI processes, such as > mpirun/mpiexec, the default number of MPI processes should be 1, correct if I > am wrong. > > Thank you in advance! > > Sincerely, > Yongzhong > > ----------------------------------------------------------- > Yongzhong Li > PhD student | Electromagnetics Group > Department of Electrical & Computer Engineering > University of Toronto > https://urldefense.us/v3/__http://www.modelics.org__;!!G_uCfscf7eWS!ZuPZtoeGFKUjdTAW0Ylzhjz0KaqtPKAf4ZOa1Xahj_4JUS8wwupZKDb_BQCWgFWPJIYRFlA3dTDHsu8H_oB-EXM$ > > <https://urldefense.us/v3/__http://www.modelics.org__;!!G_uCfscf7eWS!efVv_hPkRBEhyquXer2c8sFeGrjOtTjEGicYg2niCyfT9swzjLFyf6k4XrhKElaF-cX_Q02y9KSTRNFHPlKhXMtuzaTekCWcXgw$>
